Rock Paper Scissors Image Dataset
Versions
Rock-Paper-Scissors_raw-images
v44
Jan 11, 2023
original-images
v43
Dec 6, 2021
Version on a Monday
v42
Aug 9, 2021
Fake Version for Testing
v41
Jul 23, 2021
Demo Version 722
v40
Jul 22, 2021
Recent Version 716
v39
Jul 16, 2021
Test Version with Alan
v38
Jul 15, 2021
Test Version 123
v37
Jul 15, 2021
20210714 350pm
v36
Jul 14, 2021
Fake Version
v35
Jul 14, 2021
Test Version with Arvindh
v34
Jul 8, 2021
Test Version on a Thursday
v33
Jul 8, 2021
Test Version for Ted
v32
Jul 7, 2021
Test Version
v31
Jul 2, 2021
Version 16 V16
v30
Jul 1, 2021
Test Version with Jags
v29
Jun 30, 2021
New Version
v28
Jun 29, 2021
Test Version with Remco
v27
Jun 25, 2021
Version with Mike
v26
Jun 24, 2021
Test Version V9
v25
Jun 24, 2021
Test Version
v24
Jun 24, 2021
New Version V8
v23
Jun 23, 2021
Test Train with Mahmoud
v22
Jun 22, 2021
V8
v21
Jun 21, 2021
Generated Version 617
v20
Jun 17, 2021
Test Version V6
v19
Jun 17, 2021
Test Version
v18
Jun 15, 2021
Test Version V5
v17
Jun 15, 2021
Test Version V4
v16
Jun 10, 2021
Second Train V3
v15
Jun 10, 2021
Test Version with Burak
v14
Jun 3, 2021
Second Train V2
v13
Jun 3, 2021
First Train V1
v1
May 13, 2021
v17
Test Version V5
Generated on Jun 15, 2021
Popular Download Formats
YOLOv8
TXT annotations and YAML config used with YOLOv8.
YOLOv5
TXT annotations and YAML config used with YOLOv5.
YOLOv7
TXT annotations and YAML config used with YOLOv7.
MT-YOLOv6
MT-YOLOv6 TXT annotations used with meituan/YOLOv6.
COCO JSON
COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.
YOLO Darknet
Darknet TXT annotations used with YOLO Darknet (both v3 and v4) and YOLOv3 PyTorch.
Pascal VOC XML
Common XML annotation format for local data munging (pioneered by ImageNet).
TFRecord
TFRecord binary format used for both Tensorflow 1.5 and Tensorflow 2.0 Object Detection models.
CreateML JSON
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
Other Formats
Choose another format.
2264 Total Images
View All Images
Dataset Split
Train Set 88%
2001Images
Valid Set 8%
174Images
Test Set 4%
89Images
Preprocessing
Resize: Stretch to 416x416
Augmentations
Outputs per training example: 3
Brightness: Between -47% and +47%
Noise: Up to 9% of pixels
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